Overview

Dataset statistics

Number of variables20
Number of observations6598
Missing cells0
Missing cells (%)0.0%
Duplicate rows261
Duplicate rows (%)4.0%
Total size in memory1.0 MiB
Average record size in memory160.0 B

Variable types

NUM19
BOOL1

Reproduction

Analysis started2020-08-25 01:15:33.432908
Analysis finished2020-08-25 01:16:29.568325
Duration56.14 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

Dataset has 261 (4.0%) duplicate rows Duplicates
f14 is highly correlated with f104 and 2 other fieldsHigh correlation
f104 is highly correlated with f14 and 1 other fieldsHigh correlation
f44 is highly correlated with f104 and 1 other fieldsHigh correlation
f74 is highly correlated with f14High correlation
f59 has 151 (2.3%) zeros Zeros

Variables

f136
Real number (ℝ)

Distinct count267
Unique (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-28.25947256744468
Minimum-196.0
Maximum125.0
Zeros4
Zeros (%)0.1%
Memory size51.7 KiB
2020-08-25T01:16:29.615381image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-196
5-th percentile-119
Q1-84
median-26
Q3-10
95-th percentile84
Maximum125
Range321
Interquartile range (IQR)74

Descriptive statistics

Standard deviation61.66430041
Coefficient of variation (CV)-2.182075418
Kurtosis-0.385447099
Mean-28.25947257
Median Absolute Deviation (MAD)44
Skewness0.1796073262
Sum-186456
Variance3802.485946
2020-08-25T01:16:29.714069image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-202553.9%
 
-922543.8%
 
-232263.4%
 
-212243.4%
 
-272053.1%
 
-222043.1%
 
-261953.0%
 
-281892.9%
 
-931672.5%
 
-161121.7%
 
-94991.5%
 
-15971.5%
 
-37931.4%
 
-90871.3%
 
63831.3%
 
-95791.2%
 
64781.2%
 
-38771.2%
 
88731.1%
 
-18711.1%
 
-29681.0%
 
-17671.0%
 
-91661.0%
 
-25661.0%
 
84570.9%
 
Other values (242)340651.6%
 
ValueCountFrequency (%) 
-19640.1%
 
-19540.1%
 
-194100.2%
 
-193130.2%
 
-1922< 0.1%
 
-1751< 0.1%
 
-1671< 0.1%
 
-1633< 0.1%
 
-162120.2%
 
-161150.2%
 
ValueCountFrequency (%) 
1251< 0.1%
 
12440.1%
 
12350.1%
 
12250.1%
 
1213< 0.1%
 
1201< 0.1%
 
1193< 0.1%
 
11860.1%
 
1171< 0.1%
 
1162< 0.1%
 

f29
Real number (ℝ)

Distinct count278
Unique (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.520763867838738
Minimum-142.0
Maximum174.0
Zeros19
Zeros (%)0.3%
Memory size51.7 KiB
2020-08-25T01:16:29.826769image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-142
5-th percentile-80
Q1-44
median9
Q333
95-th percentile124
Maximum174
Range316
Interquartile range (IQR)77

Descriptive statistics

Standard deviation63.48476983
Coefficient of variation (CV)7.450596075
Kurtosis-0.447862602
Mean8.520763868
Median Absolute Deviation (MAD)46
Skewness0.2421569935
Sum56220
Variance4030.316001
2020-08-25T01:16:29.935375image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
253435.2%
 
92223.4%
 
112133.2%
 
-661912.9%
 
81792.7%
 
101592.4%
 
51472.2%
 
261472.2%
 
-651402.1%
 
141322.0%
 
-621051.6%
 
-671041.6%
 
-371001.5%
 
80991.5%
 
6951.4%
 
-64951.4%
 
126841.3%
 
7841.3%
 
24711.1%
 
-36691.0%
 
22661.0%
 
113610.9%
 
124610.9%
 
128610.9%
 
-61580.9%
 
Other values (253)351253.2%
 
ValueCountFrequency (%) 
-14260.1%
 
-1412< 0.1%
 
-140310.5%
 
-13960.1%
 
-1382< 0.1%
 
-1311< 0.1%
 
-1212< 0.1%
 
-120150.2%
 
-11970.1%
 
-118110.2%
 
ValueCountFrequency (%) 
17440.1%
 
17390.1%
 
17290.1%
 
1712< 0.1%
 
1703< 0.1%
 
1693< 0.1%
 
1682< 0.1%
 
1672< 0.1%
 
1662< 0.1%
 
16540.1%
 

f118
Real number (ℝ)

Distinct count354
Unique (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-42.35874507426493
Minimum-212.0
Maximum156.0
Zeros7
Zeros (%)0.1%
Memory size51.7 KiB
2020-08-25T01:16:30.050584image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-212
5-th percentile-204
Q1-176
median14
Q338
95-th percentile110
Maximum156
Range368
Interquartile range (IQR)214

Descriptive statistics

Standard deviation110.7014839
Coefficient of variation (CV)-2.613426901
Kurtosis-1.418015475
Mean-42.35874507
Median Absolute Deviation (MAD)61
Skewness-0.3179706987
Sum-279483
Variance12254.81853
2020-08-25T01:16:30.159366image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
372543.8%
 
361872.8%
 
221292.0%
 
381241.9%
 
231121.7%
 
-2021061.6%
 
-205961.5%
 
-199941.4%
 
-201911.4%
 
-200861.3%
 
-203851.3%
 
-198851.3%
 
25831.3%
 
-206771.2%
 
-196771.2%
 
24771.2%
 
21761.2%
 
-197751.1%
 
54731.1%
 
19711.1%
 
28711.1%
 
-204681.0%
 
26681.0%
 
52631.0%
 
59620.9%
 
Other values (329)420863.8%
 
ValueCountFrequency (%) 
-2122< 0.1%
 
-21140.1%
 
-21070.1%
 
-20990.1%
 
-208170.3%
 
-207550.8%
 
-206771.2%
 
-205961.5%
 
-204681.0%
 
-203851.3%
 
ValueCountFrequency (%) 
1561< 0.1%
 
1541< 0.1%
 
1433< 0.1%
 
142180.3%
 
141230.3%
 
140110.2%
 
139100.2%
 
138170.3%
 
1372< 0.1%
 
136190.3%
 

f28
Real number (ℝ)

Distinct count272
Unique (%)4.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-102.6659593816308
Minimum-166.0
Maximum145.0
Zeros1
Zeros (%)< 0.1%
Memory size51.7 KiB
2020-08-25T01:16:30.285642image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-166
5-th percentile-161
Q1-154
median-132
Q3-85
95-th percentile99
Maximum145
Range311
Interquartile range (IQR)69

Descriptive statistics

Standard deviation73.77823184
Coefficient of variation (CV)-0.718624092
Kurtosis3.006905272
Mean-102.6659594
Median Absolute Deviation (MAD)26
Skewness1.924734294
Sum-677390
Variance5443.227493
2020-08-25T01:16:30.391930image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-1572293.5%
 
-1341953.0%
 
-1601922.9%
 
-1561922.9%
 
-1541922.9%
 
-1581882.8%
 
-1591672.5%
 
-1531632.5%
 
-1611632.5%
 
-1551622.5%
 
-1331171.8%
 
-891101.7%
 
-1621051.6%
 
-1321051.6%
 
-881001.5%
 
-143991.5%
 
-136981.5%
 
-144941.4%
 
-135781.2%
 
-152741.1%
 
-90721.1%
 
-142691.0%
 
-149691.0%
 
-126661.0%
 
-91651.0%
 
Other values (247)343452.0%
 
ValueCountFrequency (%) 
-1662< 0.1%
 
-165150.2%
 
-164210.3%
 
-163620.9%
 
-1621051.6%
 
-1611632.5%
 
-1601922.9%
 
-1591672.5%
 
-1581882.8%
 
-1572293.5%
 
ValueCountFrequency (%) 
1452< 0.1%
 
14440.1%
 
1432< 0.1%
 
142140.2%
 
14180.1%
 
140100.2%
 
139150.2%
 
138110.2%
 
137150.2%
 
136110.2%
 

f141
Real number (ℝ)

Distinct count386
Unique (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-65.69308881479236
Minimum-290.0
Maximum188.0
Zeros2
Zeros (%)< 0.1%
Memory size51.7 KiB
2020-08-25T01:16:30.507815image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-290
5-th percentile-180
Q1-101
median-64
Q3-36
95-th percentile72
Maximum188
Range478
Interquartile range (IQR)65

Descriptive statistics

Standard deviation69.09460543
Coefficient of variation (CV)-1.051778911
Kurtosis2.320636859
Mean-65.69308881
Median Absolute Deviation (MAD)31
Skewness0.6903053233
Sum-433443
Variance4774.0645
2020-08-25T01:16:30.607997image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-272083.2%
 
-372003.0%
 
-281492.3%
 
-261462.2%
 
-361422.2%
 
-941342.0%
 
-641302.0%
 
-951041.6%
 
-931041.6%
 
-63991.5%
 
-96971.5%
 
-38951.4%
 
-35931.4%
 
-65901.4%
 
-66901.4%
 
-92751.1%
 
-49741.1%
 
-62741.1%
 
-91711.1%
 
-97711.1%
 
-61701.1%
 
-39671.0%
 
-48600.9%
 
-33590.9%
 
-25590.9%
 
Other values (361)403761.2%
 
ValueCountFrequency (%) 
-290130.2%
 
-2881< 0.1%
 
-287110.2%
 
-2862< 0.1%
 
-2711< 0.1%
 
-2622< 0.1%
 
-26160.1%
 
-25740.1%
 
-2561< 0.1%
 
-2522< 0.1%
 
ValueCountFrequency (%) 
18850.1%
 
1872< 0.1%
 
1861< 0.1%
 
1801< 0.1%
 
17970.1%
 
17840.1%
 
17740.1%
 
1762< 0.1%
 
17540.1%
 
1741< 0.1%
 

f160
Real number (ℝ)

Distinct count278
Unique (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-26.07320400121249
Minimum-136.0
Maximum192.0
Zeros34
Zeros (%)0.5%
Memory size51.7 KiB
2020-08-25T01:16:30.720162image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-136
5-th percentile-130
Q1-70
median-21
Q39
95-th percentile84
Maximum192
Range328
Interquartile range (IQR)79

Descriptive statistics

Standard deviation69.72796449
Coefficient of variation (CV)-2.674315151
Kurtosis1.007962206
Mean-26.073204
Median Absolute Deviation (MAD)37
Skewness0.6014043239
Sum-172031
Variance4861.989032
2020-08-25T01:16:30.827730image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-212413.7%
 
-202253.4%
 
-142073.1%
 
-321742.6%
 
-1291522.3%
 
-1301432.2%
 
-81271.9%
 
-1311211.8%
 
91191.8%
 
-91051.6%
 
-191031.6%
 
-291031.6%
 
-25941.4%
 
-30911.4%
 
-125891.3%
 
185891.3%
 
-128881.3%
 
-23831.3%
 
-24761.2%
 
-13741.1%
 
18691.0%
 
8681.0%
 
16671.0%
 
-133661.0%
 
-15641.0%
 
Other values (253)376057.0%
 
ValueCountFrequency (%) 
-13640.1%
 
-135120.2%
 
-134420.6%
 
-133661.0%
 
-132610.9%
 
-1311211.8%
 
-1301432.2%
 
-1291522.3%
 
-128881.3%
 
-127260.4%
 
ValueCountFrequency (%) 
1922< 0.1%
 
1902< 0.1%
 
1882< 0.1%
 
186610.9%
 
185891.3%
 
1843< 0.1%
 
18240.1%
 
1811< 0.1%
 
1801< 0.1%
 
1793< 0.1%
 

f163
Real number (ℝ≥0)

Distinct count292
Unique (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201.76023037284025
Minimum73.0
Maximum625.0
Zeros0
Zeros (%)0.0%
Memory size51.7 KiB
2020-08-25T01:16:30.941087image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum73
5-th percentile141
Q1166
median191
Q3215
95-th percentile299
Maximum625
Range552
Interquartile range (IQR)49

Descriptive statistics

Standard deviation59.52675104
Coefficient of variation (CV)0.295037089
Kurtosis9.552820604
Mean201.7602304
Median Absolute Deviation (MAD)25
Skewness2.436663549
Sum1331214
Variance3543.434089
2020-08-25T01:16:31.047152image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1591782.7%
 
1721542.3%
 
2021432.2%
 
1751402.1%
 
1761372.1%
 
1621251.9%
 
1871201.8%
 
1961171.8%
 
1931121.7%
 
2151111.7%
 
1711081.6%
 
1901081.6%
 
1951041.6%
 
1941031.6%
 
1651031.6%
 
1421021.5%
 
205961.5%
 
141921.4%
 
179881.3%
 
201851.3%
 
211841.3%
 
163831.3%
 
210821.2%
 
188811.2%
 
143771.2%
 
Other values (267)386558.6%
 
ValueCountFrequency (%) 
731< 0.1%
 
761< 0.1%
 
981< 0.1%
 
9990.1%
 
100170.3%
 
101160.2%
 
102140.2%
 
103130.2%
 
1041< 0.1%
 
1172< 0.1%
 
ValueCountFrequency (%) 
6251< 0.1%
 
6241< 0.1%
 
6151< 0.1%
 
6111< 0.1%
 
6101< 0.1%
 
6071< 0.1%
 
6021< 0.1%
 
5951< 0.1%
 
5931< 0.1%
 
5911< 0.1%
 

f50
Real number (ℝ)

Distinct count374
Unique (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-54.00181873294938
Minimum-279.0
Maximum215.0
Zeros2
Zeros (%)< 0.1%
Memory size51.7 KiB
2020-08-25T01:16:31.162069image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-279
5-th percentile-135
Q1-102
median-62
Q3-19
95-th percentile88
Maximum215
Range494
Interquartile range (IQR)83

Descriptive statistics

Standard deviation68.29416127
Coefficient of variation (CV)-1.264664096
Kurtosis2.09151944
Mean-54.00181873
Median Absolute Deviation (MAD)41
Skewness0.704498775
Sum-356304
Variance4664.092463
2020-08-25T01:16:31.261225image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-24506.8%
 
-1032213.3%
 
-191993.0%
 
-1021842.8%
 
-181672.5%
 
-201482.2%
 
-1011322.0%
 
-221191.8%
 
-211071.6%
 
-3951.4%
 
-24921.4%
 
-107901.4%
 
-23881.3%
 
-17821.2%
 
-25761.2%
 
-104741.1%
 
-100741.1%
 
-106691.0%
 
-26570.9%
 
-27530.8%
 
-96530.8%
 
-95530.8%
 
-105520.8%
 
-108520.8%
 
-94500.8%
 
Other values (349)376157.0%
 
ValueCountFrequency (%) 
-27960.1%
 
-27880.1%
 
-2762< 0.1%
 
-2753< 0.1%
 
-2731< 0.1%
 
-2711< 0.1%
 
-2631< 0.1%
 
-26260.1%
 
-2612< 0.1%
 
-2562< 0.1%
 
ValueCountFrequency (%) 
2151< 0.1%
 
2121< 0.1%
 
21150.1%
 
2091< 0.1%
 
2072< 0.1%
 
2063< 0.1%
 
2042< 0.1%
 
20340.1%
 
2002< 0.1%
 
1991< 0.1%
 

f104
Real number (ℝ)

HIGH CORRELATION

Distinct count337
Unique (%)5.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-120.37465898757199
Minimum-324.0
Maximum191.0
Zeros0
Zeros (%)0.0%
Memory size51.7 KiB
2020-08-25T01:16:31.381342image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-324
5-th percentile-306
Q1-184
median-80
Q3-53
95-th percentile36
Maximum191
Range515
Interquartile range (IQR)131

Descriptive statistics

Standard deviation109.257008
Coefficient of variation (CV)-0.9076412674
Kurtosis-0.6384238218
Mean-120.374659
Median Absolute Deviation (MAD)31
Skewness-0.5551227292
Sum-794232
Variance11937.09381
2020-08-25T01:16:31.493033image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-532213.3%
 
-542063.1%
 
-521852.8%
 
-551532.3%
 
-2931492.3%
 
-501452.2%
 
-2841191.8%
 
-491081.6%
 
-511061.6%
 
-561051.6%
 
-2921011.5%
 
-571001.5%
 
-285961.5%
 
-283871.3%
 
-48801.2%
 
-305741.1%
 
-100731.1%
 
-58711.1%
 
-304711.1%
 
-64701.1%
 
-306661.0%
 
-59620.9%
 
-66590.9%
 
-68590.9%
 
-61580.9%
 
Other values (312)397460.2%
 
ValueCountFrequency (%) 
-3241< 0.1%
 
-3201< 0.1%
 
-3192< 0.1%
 
-3181< 0.1%
 
-31680.1%
 
-31540.1%
 
-314230.3%
 
-3133< 0.1%
 
-312210.3%
 
-311240.4%
 
ValueCountFrequency (%) 
1911< 0.1%
 
1891< 0.1%
 
1521< 0.1%
 
1511< 0.1%
 
1491< 0.1%
 
1441< 0.1%
 
1431< 0.1%
 
1361< 0.1%
 
1201< 0.1%
 
1193< 0.1%
 

f59
Real number (ℝ)

ZEROS

Distinct count302
Unique (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.498029705971508
Minimum-172.0
Maximum200.0
Zeros151
Zeros (%)2.3%
Memory size51.7 KiB
2020-08-25T01:16:31.602282image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-172
5-th percentile-77
Q1-11
median19
Q362.75
95-th percentile132
Maximum200
Range372
Interquartile range (IQR)73.75

Descriptive statistics

Standard deviation61.7087875
Coefficient of variation (CV)2.328806639
Kurtosis0.5226858505
Mean26.49802971
Median Absolute Deviation (MAD)34
Skewness-0.1419383283
Sum174834
Variance3807.974454
2020-08-25T01:16:31.704242image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
352884.4%
 
01512.3%
 
361302.0%
 
31292.0%
 
91241.9%
 
-161151.7%
 
-201111.7%
 
871041.6%
 
101031.6%
 
1991.5%
 
129961.5%
 
88901.4%
 
-1881.3%
 
37851.3%
 
34851.3%
 
40761.2%
 
12761.2%
 
6751.1%
 
-11721.1%
 
-15701.1%
 
-21691.0%
 
-4681.0%
 
-50661.0%
 
7651.0%
 
5641.0%
 
Other values (277)409962.1%
 
ValueCountFrequency (%) 
-17250.1%
 
-171190.3%
 
-170120.2%
 
-16970.1%
 
-16840.1%
 
-1393< 0.1%
 
-1383< 0.1%
 
-13780.1%
 
-13650.1%
 
-1353< 0.1%
 
ValueCountFrequency (%) 
2002< 0.1%
 
1992< 0.1%
 
1981< 0.1%
 
1973< 0.1%
 
19670.1%
 
1953< 0.1%
 
1941< 0.1%
 
1931< 0.1%
 
19280.1%
 
1901< 0.1%
 

f14
Real number (ℝ)

HIGH CORRELATION

Distinct count329
Unique (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-127.93528341921794
Minimum-342.0
Maximum158.0
Zeros5
Zeros (%)0.1%
Memory size51.7 KiB
2020-08-25T01:16:31.816786image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-342
5-th percentile-290
Q1-199.75
median-92
Q3-72
95-th percentile52
Maximum158
Range500
Interquartile range (IQR)127.75

Descriptive statistics

Standard deviation101.191126
Coefficient of variation (CV)-0.7909555778
Kurtosis-0.5207416202
Mean-127.9352834
Median Absolute Deviation (MAD)26
Skewness-0.4421703967
Sum-844117
Variance10239.64398
2020-08-25T01:16:31.913028image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-2831912.9%
 
-2871502.3%
 
-831342.0%
 
-721332.0%
 
-2861302.0%
 
-741271.9%
 
-711091.7%
 
-1001061.6%
 
-2851061.6%
 
-761051.6%
 
-991041.6%
 
-821001.5%
 
-70991.5%
 
-80941.4%
 
-86931.4%
 
-81921.4%
 
-282921.4%
 
-77911.4%
 
-276901.4%
 
-84901.4%
 
-75891.3%
 
-101871.3%
 
-105831.3%
 
-85781.2%
 
-68781.2%
 
Other values (304)394759.8%
 
ValueCountFrequency (%) 
-34240.1%
 
-3411< 0.1%
 
-3402< 0.1%
 
-33850.1%
 
-33740.1%
 
-33650.1%
 
-3351< 0.1%
 
-3322< 0.1%
 
-331170.3%
 
-33060.1%
 
ValueCountFrequency (%) 
1581< 0.1%
 
1501< 0.1%
 
1471< 0.1%
 
1451< 0.1%
 
1421< 0.1%
 
1301< 0.1%
 
1291< 0.1%
 
1191< 0.1%
 
1102< 0.1%
 
1092< 0.1%
 

f155
Real number (ℝ)

Distinct count323
Unique (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.209912094574115
Minimum-143.0
Maximum379.0
Zeros25
Zeros (%)0.4%
Memory size51.7 KiB
2020-08-25T01:16:32.022652image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-143
5-th percentile-119
Q1-43
median5
Q3122
95-th percentile180
Maximum379
Range522
Interquartile range (IQR)165

Descriptive statistics

Standard deviation98.51150204
Coefficient of variation (CV)2.966328298
Kurtosis-0.02371197402
Mean33.20991209
Median Absolute Deviation (MAD)83
Skewness0.4267073794
Sum219119
Variance9704.516033
2020-08-25T01:16:32.135589image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1273725.6%
 
1241963.0%
 
1231812.7%
 
1261592.4%
 
1251372.1%
 
1211352.0%
 
21191.8%
 
1171081.6%
 
-661031.6%
 
122821.2%
 
108811.2%
 
-42791.2%
 
-51761.2%
 
-11731.1%
 
107731.1%
 
-50681.0%
 
-130641.0%
 
99631.0%
 
1631.0%
 
120600.9%
 
-43600.9%
 
-33590.9%
 
106570.9%
 
180560.8%
 
-136550.8%
 
Other values (298)401960.9%
 
ValueCountFrequency (%) 
-1432< 0.1%
 
-136550.8%
 
-135240.4%
 
-134100.2%
 
-13380.1%
 
-132210.3%
 
-131390.6%
 
-130641.0%
 
-129200.3%
 
-12880.1%
 
ValueCountFrequency (%) 
379330.5%
 
378250.4%
 
37790.1%
 
2422< 0.1%
 
2411< 0.1%
 
24040.1%
 
23880.1%
 
2371< 0.1%
 
2362< 0.1%
 
23550.1%
 

f132
Real number (ℝ)

Distinct count320
Unique (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-36.6527735677478
Minimum-140.0
Maximum255.0
Zeros33
Zeros (%)0.5%
Memory size51.7 KiB
2020-08-25T01:16:32.251720image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-140
5-th percentile-138
Q1-115
median-57.5
Q320
95-th percentile108
Maximum255
Range395
Interquartile range (IQR)135

Descriptive statistics

Standard deviation84.31638583
Coefficient of variation (CV)-2.300409427
Kurtosis-0.7250747939
Mean-36.65277357
Median Absolute Deviation (MAD)63.5
Skewness0.5367307181
Sum-241835
Variance7109.252919
2020-08-25T01:16:32.554077image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-1384677.1%
 
-1391292.0%
 
-1171111.7%
 
-1161101.7%
 
421031.6%
 
-121871.3%
 
-110851.3%
 
78801.2%
 
-136721.1%
 
81711.1%
 
-118711.1%
 
9691.0%
 
-119651.0%
 
-101641.0%
 
-120610.9%
 
-111600.9%
 
77600.9%
 
-129600.9%
 
8590.9%
 
-102590.9%
 
-86580.9%
 
10580.9%
 
11580.9%
 
-88570.9%
 
-83560.8%
 
Other values (295)436866.2%
 
ValueCountFrequency (%) 
-14060.1%
 
-1391292.0%
 
-1384677.1%
 
-137260.4%
 
-136721.1%
 
-135540.8%
 
-1342< 0.1%
 
-1331< 0.1%
 
-132180.3%
 
-131170.3%
 
ValueCountFrequency (%) 
2551< 0.1%
 
2541< 0.1%
 
2491< 0.1%
 
2471< 0.1%
 
2461< 0.1%
 
24150.1%
 
2401< 0.1%
 
2391< 0.1%
 
2381< 0.1%
 
2361< 0.1%
 

f44
Real number (ℝ)

HIGH CORRELATION

Distinct count328
Unique (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-121.6027584116399
Minimum-343.0
Maximum198.0
Zeros4
Zeros (%)0.1%
Memory size51.7 KiB
2020-08-25T01:16:32.679191image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-343
5-th percentile-319
Q1-192.75
median-74
Q3-57
95-th percentile54
Maximum198
Range541
Interquartile range (IQR)135.75

Descriptive statistics

Standard deviation111.9018942
Coefficient of variation (CV)-0.9202249659
Kurtosis-0.6220142236
Mean-121.6027584
Median Absolute Deviation (MAD)21
Skewness-0.6488812616
Sum-802335
Variance12522.03393
2020-08-25T01:16:32.780925image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-2891812.7%
 
-551712.6%
 
-561712.6%
 
-541702.6%
 
-571632.5%
 
-591622.5%
 
-581562.4%
 
-601372.1%
 
-611362.1%
 
-621081.6%
 
-531061.6%
 
-2881041.6%
 
-681001.5%
 
-67891.3%
 
-73831.3%
 
-74831.3%
 
-287831.3%
 
-52821.2%
 
-69791.2%
 
-63771.2%
 
-65761.2%
 
-64741.1%
 
-66721.1%
 
-297711.1%
 
-77711.1%
 
Other values (303)379357.5%
 
ValueCountFrequency (%) 
-34340.1%
 
-3422< 0.1%
 
-3411< 0.1%
 
-3381< 0.1%
 
-3361< 0.1%
 
-3353< 0.1%
 
-33450.1%
 
-333120.2%
 
-33250.1%
 
-331100.2%
 
ValueCountFrequency (%) 
1981< 0.1%
 
1961< 0.1%
 
1951< 0.1%
 
1941< 0.1%
 
1531< 0.1%
 
1521< 0.1%
 
1361< 0.1%
 
1121< 0.1%
 
1091< 0.1%
 
1041< 0.1%
 

f67
Real number (ℝ)

Distinct count181
Unique (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-155.73567747802363
Minimum-167.0
Maximum234.0
Zeros0
Zeros (%)0.0%
Memory size51.7 KiB
2020-08-25T01:16:32.890191image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-167
5-th percentile-167
Q1-166
median-166
Q3-165
95-th percentile-129
Maximum234
Range401
Interquartile range (IQR)1

Descriptive statistics

Standard deviation48.08447644
Coefficient of variation (CV)-0.3087569735
Kurtosis40.72579584
Mean-155.7356775
Median Absolute Deviation (MAD)0
Skewness6.318252944
Sum-1027544
Variance2312.116875
2020-08-25T01:16:32.998226image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-166389659.0%
 
-16781112.3%
 
-1655278.0%
 
-1641362.1%
 
-1611051.6%
 
-163921.4%
 
-160911.4%
 
-159721.1%
 
-162540.8%
 
-152370.6%
 
-158360.5%
 
-157340.5%
 
178300.5%
 
-149280.4%
 
-153260.4%
 
-126260.4%
 
-156240.4%
 
-145200.3%
 
-155200.3%
 
-142200.3%
 
-141200.3%
 
-127180.3%
 
-148180.3%
 
-150170.3%
 
-125170.3%
 
Other values (156)4236.4%
 
ValueCountFrequency (%) 
-16781112.3%
 
-166389659.0%
 
-1655278.0%
 
-1641362.1%
 
-163921.4%
 
-162540.8%
 
-1611051.6%
 
-160911.4%
 
-159721.1%
 
-158360.5%
 
ValueCountFrequency (%) 
2341< 0.1%
 
2331< 0.1%
 
2311< 0.1%
 
2282< 0.1%
 
2251< 0.1%
 
2231< 0.1%
 
2201< 0.1%
 
2172< 0.1%
 
21650.1%
 
21540.1%
 

f84
Real number (ℝ)

Distinct count361
Unique (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.78720824492271
Minimum-98.0
Maximum273.0
Zeros5
Zeros (%)0.1%
Memory size51.7 KiB
2020-08-25T01:16:33.150400image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-98
5-th percentile-81
Q1-35.75
median100
Q3134
95-th percentile210
Maximum273
Range371
Interquartile range (IQR)169.75

Descriptive statistics

Standard deviation96.73388016
Coefficient of variation (CV)1.42702263
Kurtosis-1.179913014
Mean67.78720824
Median Absolute Deviation (MAD)78
Skewness-0.1146811174
Sum447260
Variance9357.443571
2020-08-25T01:16:33.266926image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1941432.2%
 
-401281.9%
 
-411231.9%
 
-391101.7%
 
1101081.6%
 
-81891.3%
 
-42851.3%
 
111841.3%
 
109821.2%
 
105791.2%
 
121791.2%
 
120751.1%
 
137731.1%
 
135711.1%
 
195711.1%
 
-37691.0%
 
-80671.0%
 
108661.0%
 
107641.0%
 
193631.0%
 
124631.0%
 
-92631.0%
 
134631.0%
 
129620.9%
 
136610.9%
 
Other values (336)455769.1%
 
ValueCountFrequency (%) 
-982< 0.1%
 
-9750.1%
 
-96160.2%
 
-95200.3%
 
-94330.5%
 
-93560.8%
 
-92631.0%
 
-91160.2%
 
-9050.1%
 
-891< 0.1%
 
ValueCountFrequency (%) 
2732< 0.1%
 
27290.1%
 
27180.1%
 
27080.1%
 
269120.2%
 
2683< 0.1%
 
267100.2%
 
2641< 0.1%
 
2601< 0.1%
 
2581< 0.1%
 

f23
Real number (ℝ)

Distinct count397
Unique (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-61.6191270081843
Minimum-253.0
Maximum213.0
Zeros47
Zeros (%)0.7%
Memory size51.7 KiB
2020-08-25T01:16:33.395753image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-253
5-th percentile-216
Q1-154
median-41
Q38
95-th percentile70.15
Maximum213
Range466
Interquartile range (IQR)162

Descriptive statistics

Standard deviation94.52470947
Coefficient of variation (CV)-1.53401572
Kurtosis-0.8188060654
Mean-61.61912701
Median Absolute Deviation (MAD)59
Skewness-0.245844916
Sum-406563
Variance8934.920701
2020-08-25T01:16:33.498613image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
23044.6%
 
-421832.8%
 
211742.6%
 
-431622.5%
 
31582.4%
 
191492.3%
 
201402.1%
 
181312.0%
 
11111.7%
 
17951.4%
 
-44841.3%
 
-41821.2%
 
4691.0%
 
-40651.0%
 
10590.9%
 
16560.8%
 
7540.8%
 
9510.8%
 
-219490.7%
 
-45480.7%
 
-221470.7%
 
0470.7%
 
11460.7%
 
15440.7%
 
-185420.6%
 
Other values (372)414862.9%
 
ValueCountFrequency (%) 
-25340.1%
 
-2522< 0.1%
 
-2501< 0.1%
 
-24870.1%
 
-2471< 0.1%
 
-24550.1%
 
-24480.1%
 
-2432< 0.1%
 
-2422< 0.1%
 
-2411< 0.1%
 
ValueCountFrequency (%) 
2131< 0.1%
 
21250.1%
 
2111< 0.1%
 
2101< 0.1%
 
20960.1%
 
20460.1%
 
2032< 0.1%
 
1941< 0.1%
 
1931< 0.1%
 
1921< 0.1%
 

f108
Real number (ℝ)

Distinct count388
Unique (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-108.78872385571385
Minimum-292.0
Maximum167.0
Zeros5
Zeros (%)0.1%
Memory size51.7 KiB
2020-08-25T01:16:33.602217image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-292
5-th percentile-251
Q1-178
median-92
Q3-41
95-th percentile13
Maximum167
Range459
Interquartile range (IQR)137

Descriptive statistics

Standard deviation86.42993474
Coefficient of variation (CV)-0.7944751227
Kurtosis-0.6371522552
Mean-108.7887239
Median Absolute Deviation (MAD)65
Skewness-0.140131892
Sum-717788
Variance7470.133618
2020-08-25T01:16:33.702161image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-1202133.2%
 
-141542.3%
 
-1191512.3%
 
-151492.3%
 
-161231.9%
 
-13881.3%
 
-78831.3%
 
-118791.2%
 
-17751.1%
 
-121741.1%
 
-79661.0%
 
-12631.0%
 
-63590.9%
 
-29550.8%
 
-85540.8%
 
-80540.8%
 
-77520.8%
 
-64520.8%
 
-65520.8%
 
-76520.8%
 
-84490.7%
 
-92470.7%
 
-83470.7%
 
-19420.6%
 
-62410.6%
 
Other values (363)462470.1%
 
ValueCountFrequency (%) 
-2921< 0.1%
 
-29140.1%
 
-29050.1%
 
-289120.2%
 
-28860.1%
 
-28750.1%
 
-28640.1%
 
-285100.2%
 
-28490.1%
 
-283110.2%
 
ValueCountFrequency (%) 
1672< 0.1%
 
1652< 0.1%
 
1643< 0.1%
 
1633< 0.1%
 
1621< 0.1%
 
1601< 0.1%
 
1591< 0.1%
 
1583< 0.1%
 
1561< 0.1%
 
1531< 0.1%
 

f74
Real number (ℝ)

HIGH CORRELATION

Distinct count386
Unique (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-104.8208548044862
Minimum-333.0
Maximum172.0
Zeros5
Zeros (%)0.1%
Memory size51.7 KiB
2020-08-25T01:16:33.812410image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-333
5-th percentile-248
Q1-178
median-82
Q3-57
95-th percentile45
Maximum172
Range505
Interquartile range (IQR)121

Descriptive statistics

Standard deviation86.98407808
Coefficient of variation (CV)-0.8298356109
Kurtosis-0.04964489983
Mean-104.8208548
Median Absolute Deviation (MAD)32
Skewness-0.2998622213
Sum-691608
Variance7566.229839
2020-08-25T01:16:33.908003image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-2471842.8%
 
-2461802.7%
 
-2481352.0%
 
-621001.5%
 
-191941.4%
 
-245931.4%
 
-192921.4%
 
-60881.3%
 
-194861.3%
 
-64851.3%
 
-67851.3%
 
-69841.3%
 
-63831.3%
 
-58801.2%
 
-59761.2%
 
-61731.1%
 
-66721.1%
 
-68701.1%
 
-57701.1%
 
-75691.0%
 
-95681.0%
 
-65681.0%
 
-193681.0%
 
-70661.0%
 
-74651.0%
 
Other values (361)436466.1%
 
ValueCountFrequency (%) 
-3333< 0.1%
 
-33240.1%
 
-3302< 0.1%
 
-3293< 0.1%
 
-3283< 0.1%
 
-3273< 0.1%
 
-3263< 0.1%
 
-3252< 0.1%
 
-3242< 0.1%
 
-3232< 0.1%
 
ValueCountFrequency (%) 
1721< 0.1%
 
1691< 0.1%
 
1671< 0.1%
 
1651< 0.1%
 
1631< 0.1%
 
1611< 0.1%
 
1471< 0.1%
 
1253< 0.1%
 
1242< 0.1%
 
1233< 0.1%
 

target
Boolean

Distinct count2
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.7 KiB
0
5581
1
 
1017
ValueCountFrequency (%) 
0558184.6%
 
1101715.4%
 

Interactions

2020-08-25T01:15:35.097134image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:35.241039image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:35.382963image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:35.528861image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:35.670472image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:35.812674image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:35.953836image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:36.091233image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:36.231462image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:36.367951image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:36.514659image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:36.652000image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:36.793334image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:36.946579image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:37.089101image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:37.240866image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:37.391877image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:37.528392image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:37.664484image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:37.801878image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:37.951148image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:38.094387image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:38.241465image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:38.387437image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:38.527546image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:38.674703image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:39.012462image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:39.153468image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:39.297687image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:39.443861image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:39.584917image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:39.730715image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:39.883398image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:40.020424image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:40.171026image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:40.320749image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:40.458832image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:40.596290image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:40.729365image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:40.879597image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:41.029542image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:41.179634image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:41.343915image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:41.487531image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:41.643478image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:41.794312image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:41.955590image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:42.111794image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:42.270482image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:42.414941image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:42.563013image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:42.722502image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:42.869220image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:43.029540image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:43.183995image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:43.327023image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:43.670364image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:43.818733image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:43.966938image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:44.111615image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:44.260514image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:44.407988image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:44.549399image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:44.701202image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:44.842942image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:44.985551image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:45.125896image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:45.275002image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:45.414928image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:45.558361image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:45.712711image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:45.854433image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:46.022605image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:46.173531image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:46.317323image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:46.457752image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:46.594760image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:46.733995image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:46.879060image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:47.025816image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:47.168047image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:47.306832image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:47.452555image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:47.591876image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:47.727910image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:47.863411image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:48.008198image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:48.331841image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:48.474632image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:48.621276image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:48.756118image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:48.905032image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:49.048202image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:49.180883image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:49.312086image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:49.450747image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:49.599431image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:49.746033image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:49.903782image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:50.053971image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:50.199101image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:50.349777image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:50.495804image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:50.639107image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:50.782737image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:50.931968image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:51.070473image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:51.213868image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:51.364749image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:51.511385image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:51.662786image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:51.809895image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:51.946925image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:52.086639image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:52.226924image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:52.370269image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:52.513596image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:52.841942image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:52.976736image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:53.108915image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:53.249591image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:53.380193image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:53.514246image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:53.649098image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:53.793882image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:53.928753image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:54.067576image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:54.216134image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:54.347109image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:54.488761image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:54.626571image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:54.751853image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:54.884758image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:55.009445image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:55.145101image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:55.285489image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:55.424746image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:55.564191image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:55.694163image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:55.828813image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:55.959025image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:56.094009image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:56.227548image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:56.369049image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:56.504703image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:56.640266image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:56.797127image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:56.928657image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:57.298922image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:57.477116image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:57.610438image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:57.737264image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:57.865457image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:58.010540image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:58.152204image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:58.294647image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:58.431309image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:58.564767image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:58.707942image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:58.851820image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:58.987054image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:59.125398image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:59.268998image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:59.401529image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:59.535953image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:59.689329image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:59.826295image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:15:59.969015image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:00.111224image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:00.239456image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:00.368227image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:00.497032image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:00.646590image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:00.794373image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:00.940055image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:01.087220image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:01.228426image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:01.376808image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:01.517318image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:01.835235image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:01.973779image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:02.126341image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:02.267996image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:02.412451image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:02.568366image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:02.719865image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:02.886476image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:03.040181image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:03.182364image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:03.324566image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:03.466266image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:03.603020image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:03.736639image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:03.892482image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:04.027154image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:04.159623image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:04.303984image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:04.437867image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:04.574946image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:04.706655image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:04.844977image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:04.971813image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:05.101398image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:05.244431image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:05.374017image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:05.514008image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:05.652288image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:05.785504image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:05.911548image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:06.038823image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:06.366986image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:06.506668image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:06.644664image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:06.783359image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:06.917407image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:07.058958image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:07.197001image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:07.333947image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:07.469727image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:07.609087image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:07.741775image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:07.879089image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:08.032435image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:08.167729image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:08.316295image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:08.462732image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:08.593256image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:08.721924image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:08.859018image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:09.004934image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:09.153486image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:09.304800image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:09.453963image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:09.602208image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:09.761662image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:09.913007image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:10.059874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:10.208430image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:10.364801image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:10.512841image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:10.851547image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:11.009698image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:11.156193image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:11.316952image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:11.473080image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:11.614689image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:11.758274image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:11.902960image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:12.036965image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:12.174364image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:12.316054image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:12.453569image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:12.589990image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:12.727232image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:12.862112image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:12.995912image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:13.130795image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:13.280616image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:13.411746image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:13.546203image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:13.689640image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:13.837395image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:13.984052image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:14.126517image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:14.260356image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:14.394231image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:14.528907image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:14.683907image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:14.837696image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:14.997322image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:15.347168image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:15.498986image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:15.663633image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:15.816828image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:15.970437image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:16.137652image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:16.316722image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:16.467828image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:16.618425image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:16.782628image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:16.938385image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:17.102447image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:17.269743image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:17.417564image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:17.565505image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:17.710865image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:17.859551image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:18.009710image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:18.160741image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:18.319959image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:18.469761image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:18.622667image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:18.767598image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:18.915616image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:19.063936image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:19.221414image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:19.364122image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:19.524502image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:19.698356image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:20.027266image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:20.183026image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:20.339572image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:20.483235image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:20.627282image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:20.766838image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:20.897395image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:21.032603image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:21.172527image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:21.304200image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:21.432919image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:21.569438image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:21.702075image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:21.832050image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:21.962016image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:22.100159image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:22.229968image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:22.356117image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:22.497808image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:22.623451image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:22.764293image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:22.896847image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:23.022089image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:23.143409image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:23.271587image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:23.410521image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:23.547651image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:23.684031image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:23.828347image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:23.960729image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:24.102006image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:24.421354image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:24.554666image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:24.693043image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:24.832880image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:24.959688image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:25.090574image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:25.224839image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:25.350106image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:25.491072image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:25.631359image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:25.753984image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:25.878190image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:26.004539image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:26.139113image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:26.269068image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:26.409061image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:26.543682image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:26.675596image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:26.816370image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:26.947397image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:27.077027image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:27.206934image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:27.342040image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:27.468997image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:27.601911image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:27.748697image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:27.881813image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:28.028088image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:28.166968image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:28.292137image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:28.417793image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Correlations

2020-08-25T01:16:34.053361image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-08-25T01:16:34.364591image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-08-25T01:16:34.670873image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-08-25T01:16:34.984228image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-08-25T01:16:28.903987image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T01:16:29.387395image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Sample

First rows

f136f29f118f28f141f160f163f50f104f59f14f155f132f44f67f84f23f108f74target
0-19.0-67.061.0-89.0-149.0-7.0156.0-2.0-306.0-4.0-299.0128.0-118.0-314.0-166.0112.0-67.0-35.0-256.01
1-94.032.037.0-91.0-26.052.0169.0-179.0-305.048.0-281.0115.0-128.0-318.0-166.0127.02.0-117.0-189.01
2-93.022.038.0-88.0-26.057.0165.0-128.0-305.040.0-283.077.0-129.0-317.0-166.055.02.0-119.0-190.01
3-93.032.037.0-91.0-26.052.0168.0-180.0-306.047.0-282.0115.0-128.0-319.0-166.0128.02.0-118.0-191.01
4-93.031.037.0-91.0-26.052.0168.0-180.0-306.047.0-282.0115.0-128.0-319.0-166.0128.02.0-118.0-191.01
5-93.021.038.0-88.0-26.056.0164.0-126.0-306.040.0-284.076.0-129.0-318.0-166.055.03.0-120.0-191.01
6-23.022.023.0-134.0-94.055.0165.0-129.0-303.041.0-285.074.0-129.0-298.0-166.055.0-42.0-15.0-244.01
7-23.033.019.0-136.0-90.050.0169.0-180.0-305.049.0-285.0117.0-128.0-304.0-166.0128.0-40.0-13.0-246.01
8-23.033.019.0-136.0-90.050.0169.0-180.0-305.048.0-285.0117.0-128.0-304.0-166.0128.0-40.0-13.0-246.01
9-23.022.023.0-134.0-94.055.0165.0-129.0-303.041.0-285.074.0-129.0-298.0-166.055.0-42.0-15.0-244.01

Last rows

f136f29f118f28f141f160f163f50f104f59f14f155f132f44f67f84f23f108f74target
6588106.09.057.0-151.0-42.0-10.0195.0-87.0-51.0-21.0-124.0127.0-97.0-76.0-166.0-12.022.0-145.0-72.00
6589-112.09.0107.0128.0-62.0-8.0195.0-83.0-52.0-21.0-112.0127.0-99.0-80.0-166.0-10.010.0-139.0-47.00
6590106.011.048.0-149.0-38.014.0187.0-80.0-52.0-16.0-130.07.0-86.0-80.0-166.0-30.023.0-152.0-84.00
6591-137.09.052.071.0-42.0-4.0195.0-64.0-57.0-22.0-93.0127.0-102.0-93.0-166.0-8.0-24.0-121.0-47.00
6592-110.011.0105.0131.0-59.014.0188.0-76.0-54.0-17.0-117.07.0-88.0-84.0-166.0-27.013.0-145.0-52.00
6593-23.0-51.0-187.0-153.0-124.0-14.0171.0-51.0-118.064.0-77.0124.01.0-101.0-166.0-69.0-198.0-222.0-55.00
6594-28.0-41.0-197.0-160.0-125.0-9.0158.0-44.0-112.075.0-74.0-49.0-75.0-90.0-166.0-73.0-201.0-192.0-61.00
6595-28.0-59.0-203.0-161.0-130.0-8.0159.0-18.0-119.025.0-82.0-47.0-117.0-108.0-165.0-55.0-197.0-162.0-60.00
6596-23.0-63.0-194.0-154.0-113.0-14.0171.0-20.0-127.015.0-86.0124.0-6.0-119.0-166.0-48.0-180.0-202.0-55.00
6597-23.063.0-191.0-154.0-125.0-14.0171.0-39.0-121.0150.0-79.0124.0-4.0-105.0-110.0-58.0-196.0-207.0-56.00

Duplicate rows

Most frequent

f136f29f118f28f141f160f163f50f104f59f14f155f132f44f67f84f23f108f74targetcount
25-92.0-67.038.0-84.0-26.0-125.0185.0-2.0-310.0-4.0-283.0-136.0-139.0-325.0-166.0111.03.0-122.0-194.008
55-86.0-64.037.0-89.0-29.0185.0159.0-2.0-302.03.0-274.0156.0-112.0-316.0-159.0106.01.0-119.0-189.007
36-92.025.036.0-92.0-28.0-128.0215.0-103.0-283.035.0-273.0-11.073.0-293.0-166.0-42.01.0-118.0-190.006
39-92.025.038.0-85.0-26.0-125.0189.0-101.0-284.035.0-276.0-136.0-139.0-297.0-166.0-40.03.0-121.0-194.006
42-92.026.037.0-88.0-27.0-131.0400.0-103.0-285.035.0-275.013.0-136.0-297.0-166.012.02.0-120.0-192.006
54-86.0-64.037.0-90.0-30.0185.0162.0-2.0-300.03.0-273.0156.0-112.0-315.0-159.0105.00.0-119.0-189.005
110-21.025.025.0-132.0-96.0-124.0190.0-101.0-293.035.0-287.0-135.0-139.0-288.0-166.0-40.0-43.0-16.0-246.005
127-20.025.019.0-136.0-92.0-128.0217.0-103.0-292.035.0-286.0-11.075.0-289.0-166.0-42.0-41.0-13.0-248.005
9-94.0-66.035.0-89.0-26.0-93.0118.0-2.0-312.0-2.0-285.0377.0-136.0-326.0-166.0112.03.0-119.0-196.004
10-94.025.036.0-89.0-26.0-94.0119.0-101.0-285.034.0-278.0378.0-136.0-300.0-166.0-37.03.0-119.0-195.004